Computer Science

Dr Yanda Meng

Dr Yanda Meng

Lecturer
Computer Science

I am a Lecturer (Assistant Professor) at the University of Exeter, Computer Science Department. I am now also an Honorary Lecturer at the Cardiovascular & Metabolic Medicine Department, University of Liverpool.

I did my PhD with Prof Yalin Zheng and Prof Xiaowei Huang at the Eye and Vision Science Department at the University of Liverpool, with a short-term research visit to Prof Jens Rittscher's group at the Biomedical Engineering Institute, University of Oxford. Then, I did a post-doc with Prof Yalin Zheng and Dr Nicholas AV Beare in Liverpool on a Wellcome Trust-funded AI-assisted OCT device for cerebral malaria disease diagnosis and prognosis. I work closely with Dr Alam Uazman on CCM image-based diabetes neuropathy diagnosis and Prof Gregory Lip on cardiovascular diseases early detection.

 

 

I am looking for self-motivated Ph. D. students. If you are interested in working with me, please email me about your background (CV, transcripts, etc..)

Some useful links: (1) EPSRC PhD Studentships; (2) Centre for Doctoral Training in Enviornmental Intelligence; (3) China Scholarship Council and University of Exeter PhD Scholarships

 

 

News:

  • Sep 2024, One paper, 'MR2 -Net: Retinal OCTA Image Stitching via Multi-Scale Representation Learning and Dynamic Location Guidance', is accepted by the IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI).
  • July 2024, One industry-funded 3-year PhD studentship at the UK tuition fee and UKRI stipend rate is available in my group. The application deadline is 25th Aug 2024. link.
  • July 2024, One paper, ‘Artificial intelligence – based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes - The Silesia Diabetes Heart Study’ is accepted by Cardiovascular Diabetology.
  • July 2024, Acceptance of a UK-rate full PhD studentship as PI, funded by Liverpool Heart and Chest Hospital NHS Trust Foundation and Liverpool Centre for Cardiovascular Science; the student is expected to start in January 2025.
  • June 2024, One paper, ‘AI-Driven Generalised Polynomial Transformation Models for Unsupervised Fundus Image Registration,’ is accepted by Frontiers in Medicine, section Ophthalmology.
  • June 2024, Two papers were accepted by MICCAI2024, ‘CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting’ and ‘Multi-disease Detection in Retinal Images Guided by Disease Causal Estimation’.
  • May 2024, One paper, ‘Self-Guided Adversarial Network for Domain Adaptive Retinal Layer Segmentation,’ is accepted by IEEE Transactions on Instrumentation & Measurement.
  • May 2024, Acceptance of 2024 SeedCorn Fund of Health Technologies@Exeter as PI.
  • May 2024, One paper, ‘The impact of reasoning step length on large language models’, is accepted by ACL 2024 as Findings; congrats to Mingyu and Qinkai as their first-author publications!
  • April 2024, One industry-funded 3.5-year PhD studentship at the UK tuition fee and UKRI stipend rate is available in my group. The deadline to apply is 15th May 2024. link.
  • April 2024, One paper, ‘Multi-granularity learning of explicit geometric constraint and contrast for label-efficient medical image segmentation and differentiable clinical function assessment’, is accepted by Medical Image Analysis.
  • April 2024, Acceptance of an international full PhD studentship as PI, funded by Liverpool Centre for Cardiovascular Science. The student is expected to start in September 2024.

 

 

 

Publication (See my google scholar for more details):
I have published more than 30 papers in peer-reviewed journals and conferences and first-authored more than 15 publications at prestigious AI Computer Vision, Medical Image Analysis journals/conferences,
 
Selected publications (* means equal contribution, † means the corresponding author):
 
  • Yanda Meng, et al. Multi-Granularity Learning of Explicit Geometric Constraint and Contrast for Label-Efficient Medical Image Segmentation and Differentiable Clinical Function Assessment. Medical Image Analysis.
  • Yanda Meng, et al. Bilateral Adaptive Graph Convolutional Network on CT-based COVID-19 Diagnosis with Uncertainty-Aware Consensus-Assisted Multiple Instance Learning. Medical Image Analysis.
  • Yanda Meng, et al. Dual Consistency Enabled Weakly and Semi-Supervised Optic Disc and Cup Segmentation with Dual Adaptive Graph Convolutional Networks. IEEE Transactions on Medical Imaging.
  • Yanda Meng, et al. Graph-based Region and Boundary Aggregation for Biomedical Image Segmentation. IEEE Transactions on Medical Imaging.
  • Frank G Preston*, Yanda Meng*, et al. Artificial intelligence utilising corneal confocal microscopy for the diagnosis of peripheral neuropathy in diabetes mellitus and prediabetes. Diabetologia (front cover).
  • *Katarzyna Nabrdalik, *Krzysztof Irlik, *Yanda Meng, et al. Artificial intelligence – based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes - The Silesia Diabetes Heart Study. Cardiovascular Diabetology.
  • Yanda Meng, et al. Transportation Object Counting with Graph-Based Adaptive Auxiliary Learning. IEEE Transactions on Intelligent Transportation System.
  • Yanda Meng, et al. Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neurapathy: A Binary Classification Model. Journal of Clinical Medicine.
  • Alastair Patefield*, Yanda Meng*, et al. Deep-Learning using preoperative AS-OCT predicts graft detachmeng in DMEK. Translational Vision Science and Technology.
  • Jianyang Xie, Yanda Meng†, et al. Dynamic Semantic-based Graph Convolution Network for Skeleton-based Human Action recognition. AAAI 2024.
  • Qinkai Yu, .., Yanda Meng†. ‘CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting’ MICCAI 2024
  • Yanda Meng, et al. Spatial Uncertainty-Aware Semi-Supervised Crowd Counting. ICCV 2021.
  • Yanda Meng, et al. Regression of Instance Boundary by Aggregated CNN and GCN. ECCV 2020.
  • Yanda Meng, et al. CNN-GCN Aggregation Enabled Boundary Regression for Biomedical Image Segmentation. MICCAI 2020 (early accept).
  • Yanda Meng, et al. Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency. MICCAI 2022 (early accept).
  • Yanda Meng, et al. BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation. BMVC 2021 (oral).
  • Yanda Meng, et al. Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-aware Contrastive Learning. PRCV 2023.
  • Yanda Meng, et al. Diagnosis of Diabetic Neuropathy by Artificial Intelligence using Corneal Confocal Microscopy. EAsDEC 2022
 
 
 
Academic Services:
  • Lead Guest Editor: Frontiers in Medicine Special Issue on Efficient Artificial Intelligence (AI) in Ophthalmic Imaging
  • Reviewer:
    Conference: ICCV, CVPR, ECCV, AAAI, MICCAI, MIDL
    Journal: MedIA, IEEE-TMI, IJCV, IEEE-TIP, IEEE-TCSVT, IEEE-JBHI, npj Digital Medicine, npj Parkinson's Disease, Medical Physics, Frontier in Medicine, Artificial Intelligence in Medicine, Computerized Medical Imaging and Graphics, Computers in Biology and Medicine, etc.

 

 

 

 
 

 

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